fit.nnetwork: Function to fit neural network to a data.frame or an...
In isglobal-brge/nlOmicAssoc: non-linar omic association
Description
Neural networks are adjusted for each row in data using package nnet
Usage
1
2
fit.nnetwork(data = data_m, vars_df = vars_df, size = 2L, cores = 1L,
verbose = FALSE, ...)
Arguments
data
ExpressionSet or data.frame with samples as columns and observations as rows could be an ExpressionSet(modif!)
vars_df
data.frame with sampes as rows and variables as columns
size
nnet param: number of units in the hidden layer. Can be zero if there are skip-layer units
cores
cores in case of parallelization (no windows)
verbose
logical to verbose (comment) the steps of the function, default(FALSE)
isglobal-brge/nlOmicAssoc documentation built on May 9, 2019, 8:16 a.m.
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Description
Neural networks are adjusted for each row in data using package nnet
Usage
1 2 | fit.nnetwork(data = data_m, vars_df = vars_df, size = 2L, cores = 1L,
verbose = FALSE, ...)
|
Arguments
data |
|
vars_df |
data.frame with sampes as rows and variables as columns |
size |
nnet param: number of units in the hidden layer. Can be zero if there are skip-layer units |
cores |
cores in case of parallelization (no windows) |
verbose |
logical to verbose (comment) the steps of the function, default(FALSE) |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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